Do you know our website name TekstoSense is derived using Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) network: a special type of RNN? Is it not fun ? Yes it is. Teksto in Esperanto means Text. Tekstosense is one stop apis hub for all the text analytics need. We want our users to focus on their market proposition and differentiation and we provides all possible building blocks for text analytics ecosystem to reduce their time to market.
Have you ever faced twin tombstone problems of text analytics area i.e. accuracy and speed? Have you ever looked for free production grade text analytics APIs which performs out the box and satisfies your need? If your answer is yes your search ends here. TekstoSense is a suit of text analytics APIs which is based on unsupervised, semi-supervised and supervised machine learning algorithms.
- CLI: Control your TekstoSense APIs from the command line just like Neo in The Matrix.
- REST API: TekstoSense can be operated with its RESTful API for maximum flexibility.
- Rule Based Configurations: Configs are always available to change based on your requirement at run time.
- Scalability: Distributed by nature, TekstoSense APIs scales horizontally simply by adding nodes. Processing layer is based on Spark.
- Performance: TekstoSense APIs handles load with ease by scaling the core.
- Dependency: Simple to use with minimal dependencies.
- Distribution: Single Mode APIs with Apache license and Batch Mode APIs with Commercialised license.
- Deployable: Deployed on google cloud with kubernate. Plug and play for on-premise or cloud distribution.
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We generally use Opennlp or Stanford NLP or LingPipe or NLTK for our text analytics need but these are just enablers framework not an out of the box APIs framework to build use cases. Similarly we have lots of Deep-Learning frameowrk. To develop use cases we need to build bridges between two pillars of text analytics , NLP at one side and Machine Learning at the other side. TekstoSense bridge that gap and provides ready to use text analytics API.
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If you ever hesitated to use unsupervised algorithm based solution into your product due to unsatisfactory accuracy then simply forget the past and forge toward the TekstoSense. It provides high accuracy for its algorithms and APIs. TekstoSense provides usecase centric APIs.
- pdf-segmenter : Unsupervised algorithm for identifying pdf segment.
- opennlp-enhancer : Extended opennlp framework with main focus on memory optimization and NER support
- word-root-finder : Personalised word root finder
You can find a detailed Roadmap of TekstoSense on the Wiki.
All our APIs are hosted as REST-Service on google cloud for user verification. Batch mode APIs are only available on request. [Demo] (http://apis.tekstosense.com)
Different components are tagged under different license ranging from Apcahe 2.0 , GNU to Commercial License. We strive hard to make most of our base component as Apache license for wider use.
Copyright 2016 TekstoSense
## Apache License(2.0)
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
## Commercial license
TekstoSesne few component is licensed under Commercial license. It is appropriate for development of proprietary/commercial
software where you do not want to share any source code with third parties or otherwise cannot comply with the terms
of the GPL.
To obtain the commercial license please contact [email protected]